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Multi-objective optimization model in the vehicle suspension system development process

In order to improve conceptual phase of vehicle development, this research is focused on development of new multi-objective optimization model for determining the optimal parameters of the suspension system. In this research emphasis is on the development of suspension system from the viewpoint of full vehicle dynamics behaviour. The new optimization model consists of the integration of fast simulation tools with a suitable degree of accuracy for analysis of suspension system kinematics and analysis of vehicle dynamics into multi-objective optimization environment. The necessary steps that proceed to development of optimization model are identification of influence parameters, definition of criteria for the evaluation of vehicle dynamic characteristics in different test procedures and selection of multi-objective optimization algorithms, primarily contemporary evolutionary algorithms. In comparison of the algorithms, the best results in terms of convergence, number of solutions, short computing time and Pareto front approximation were achieved with the FMOGA-II algorithm.

evolutionary algorithms; multi-objective optimization; suspension system parameters; vehicle dynamics

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